Copyright 2012 Taxonomy Strategies. All rights reserved. Metadata Interoperability

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1 Taxonomy Strategies LLC March 15, 2012 Copyright 2012 Taxonomy Strategies. All rights reserved. Metadata Interoperability X

2 Agenda Interoperability Dublin Core Dates, roles and topics Tagging assets Tools for automating tagging 2

3 Interoperability The ability of diverse systems and organizations to work together by exchanging information. Semantic interoperability is the ability to automatically interpret the information exchanged meaningfully and accurately. 3

4 Asset Cost Interoperability ROI Content assets are expensive to create so it s critical that they can be found, so they can be used and re-used. Every re-use decreases the content asset creation cost and increases the asset value Asset Uses 4

5 Interoperability (2) If content assets are so important, why can t they be found? They contain no searchable text, e.g., images. They exist in different applications, file shares and/or desktops. Other reasons? When they are found why can t content assets be reused? When there are multiple versions, it s difficult to choose which one to use. The usage rights may not be clear. Other reasons? 5

6 Interoperability (3) Digital content assets are sourced from multiple applications and locations Desktop applications Enterprise content management applications Product lifecycle management (PLM) applications Product information management (PIM) applications Third party contractors systems Other divisions and departments in your organization Marketing and Communications servers Other applications and locations? 6

7 Interoperability vision I want to easily find any content assets in a particular format that can be used for a specific purpose regardless of where they are located. Challenges: How to align different metadata properties E.g., Author and Creator; Title and Caption; Location and Setting; etc. How to align different vocabularies E.g., CA and California; RiM and Research in Motion; etc. 7

8 Complexity What is metadata? Metadata provides enough information for any user, tool, or program to find and use any piece of content. Subject metadata What, Where & Why: Subject, Type, Coverage Use metadata When & How: Date, Language, Rights Asset metadata Who: Identifier, Creator, Title, Description, Publisher, Format, Contributor Relational metadata Links between and to: Source, Relation Enabled Functionality 8

9 Complexity What is metadata Metadata provides enough information for any user, tool, or program to find and use any piece of content. Subject metadata What, Where & Why: Subject, Type, Coverage Better navigation & discovery Use metadata When & How: Date, Language, Rights Asset metadata Who: Identifier, Creator, Title, Description, Publisher, Format, Contributor More efficient editorial process Relational metadata Links between and to: Source, Relation Enabled Functionality 9

10 But Dublin Core is a little more complicated Elements 1. Identifier 2. Title 3. Creator 4. Contributor 5. Publisher 6. Subject 7. Description 8. Coverage 9. Format 10. Type 11. Date 12. Relation 13. Source 14. Rights 15. Language Refinements Abstract Access rights Alternative Audience Available Bibliographic citation Conforms to Created Date accepted Date copyrighted Date submitted Education level Extent Has format Has part Has version Is format of Is part of Is referenced by Is replaced by Is required by Issued Is version of License Mediator Medium Modified Provenance References Replaces Requires Rights holder Spatial Table of contents Temporal Valid Encodings Box DCMIType DDC IMT ISO3166 ISO639-2 LCC LCSH MESH Period Point RFC1766 RFC3066 TGN UDC URI W3CTDF Types Collection Dataset Event Image Interactive Resource Moving Image Physical Object Service Software Sound Still Image Text 10

11 and Dublin Core has gotten more abstract DCAM (Dublin Core Abstract Model) Singapore Framework 11

12 So why Dublin Core? Dublin Core is a de-facto standard across many other systems and standards RSS (1.0), OAI (Open Archives Initiative) Inside organizations SharePoint, ECMS, DAMS, etc. Mapping to DC elements from most existing schemes is simple Metadata already exists in enterprise applications MS Office, SharePoint, MarkLogic, OpenText, Documentum, SAP, etc. Taxonomies, Vocabularies, Ontologies Per-Source Data Types, Access Controls, etc. Dublin Core Source: Todd Stephens, BellSouth 12

13 Dublin Core is the top vocabulary in the linked data cloud 13

14 Dates, roles and topics Explicit dates associated with an event in the life cycle of a resource. Best practice: YYYY-MM-DD (W3C DTF Profile of ISO 8601) Property Description Set By date.added Date the asset was first added to the DAM. DAM date.lastmodified date.reviewed date.nextreviewed date.embargoed date.subject Date the asset was last reviewed for accuracy and relevance. Used for provenance and to validate content or rights. Date the content was last reviewed for accuracy and relevance. Used for provenance, and to compute a future date to recheck the content. Date of next scheduled review for accuracy and relevance. Date and time that content is scheduled to become available on the site. Content can be prepared in advance and system will push it out once the embargo date is reached. Date of the event, data, or other information depicted in the asset. Used for search and recall purposes. (This is not the date the asset was uploaded or last updated). DAM DAM Rule Manual Manual 14

15 Admin Add Edit Delete Approve Review Dates, roles and topics Role Administrator Approver Contributor Description Technical administration of the DAM. Generally allowed to do anything, to keep the system running and up-todate. Senior DAM staff with the authority to approve assets for publication. In small shops Contributors may also be Approvers. Larger shops, and those using outsider contractors will have many Contributors but just a few Approvers. Editorial staff with authority to contribute new assets to the DAM. Their work must be approved by an Approver before it can be published. Administrators have the authority to approve content for publication, but only as an exception not the rule. Y Y Y Y Y Y N Y Y Y Y Y N Y Y N N Y 15

16 Dates, roles and topics Locations Concepts Expertise Events Objects People (Types) People (Roles) Setting Classroom & Seminar Room Common Area Campus Exteriors Housing Laboratory Office Clinical Community Nature Community Pharmacy Culture Campuses & Locations Bay Area San Francisco National International Laurel Heights Mission Bay Campus Mission Center Mount Zion Campus Parnassus Campus Caring for Patients Collaboration Concentration Conducting Science Contemplation Diversity Growth and Progress Happiness Innovation Leadership Learning Passion Questioning Recreation Service Socializing Systems & Organizations Teaching/Presenting Unhappiness Basic and Applied Research Health Policy Research Clinical Research Pharmacy Practice Research Awards Ceremonies Community Outreach Conferences & Courses Graduations, Professional Program Graduations, Graduate Programs Homecomings & Reunions Orientations & Registrations Parties & Receptions Recruitment Students Organizations & Extracurricular Activities White Coat Ceremonies Lab Equipment Research Core Equipment Computing, Networking & IT Equipment Medicines, Medicine Containers, & Delivery Devices Medical Devices Transportation Vehicles Lab coats Infants Children Youth Families Elderly Patients Researchers Clinicians Teachers University Students Alumnus Associate / Assistant Dean Board of Advisors Chair Dean Donor Faculty Friend Graduate Students PharmD Students Postdocs, professional Postdocs, science Staff / Administrator Visitors Other UC 16

17 Semantic relationships among topics Projects Has A Has A Has A Has A Has A Has A Project No Contract Type Start Date Closeout Date Status Countries Has A Is Part Of Country Code Region 17

18 Semantic relationships among topics Products Location Person Other Facets Is Part Of Is A Is A Is A Product Line Technology Application Industry Solution Oracle events Oracle press releases 18

19 The Tagging Problem How are we going to populate metadata elements with complete and consistent values? What can we expect to get from automatic classifiers? 19

20 Cheap and Easy Metadata Some fields will be constant across a group or collection of content items E.g., project, project no, contract type, start date, closeout date, status, country and region E.g., product, product line, technology, application and industry solution In the context of a single group or collection those kinds of elements may add little value, but they add tremendous value when many groups or collections are brought together into one place, and they are cheap to create and validate. 20

21 Methods used to create & maintain metadata 80% 71% 70% 60% 57% 50% 43% 43% 40% 30% 20% 10% 0% Forms Distributed Production Centralized production Not Automated Web-based forms are most widely used: Distributed resource origination metadata tagging Centralized clean-up and metadata entry. Source: CEN/ISSS Workshop on Dublin Core. 21

22 Tagging considerations Who should tag assets? Producers or editors? Taxonomy is often highly granular to meet task and re-use needs, but with detailed taxonomy it s difficult to get complete and consistent tags. The more tags there are (and the more values for each tag), the more hooks to the content, but the more difficult it is to get completeness and consistency. If there are too many tags or tags are too detailed, producers will resist and use general tags (if available) Vocabulary is often dependent on originating department, but the lingo may not be readily understood by people outside the department (who are often the users). 22

23 Tagging considerations (2) Automatic classification tools exist, and are valuable, but results are not as good as people can do. Semi-automated is best. Degree of human involvement is a cost/benefit tradeoff. 23

24 Tools for tagging Vendor Taxonomy Editing Tools URL Autonomy Collaborative Classifier ConceptSearching Data Harmony M.A.I. TM (Machine Aided Indexing) Microsoft Office Properties Intelligent Topic Manager nstein TME (Text Mining Engine) PoolParty Extractor Semaphore Classification and Text Mining Server Temis Luxid for Content Enrichment office.microsoft.com/en-us/access-help/view-or- change-the-properties-for-an-office-file- HA aspx?CTT=1 poolparty.biz/products/poolparty-extractor/

25 Joseph Busch (415) twitter.com/joebusch Thank You QUESTIONS 26